One Social Movement, Two Social Media Sites: A Comparative Study of Public Discourses

2017 ◽  
Vol 26 (4-6) ◽  
pp. 807-836 ◽  
Author(s):  
Yubo Kou ◽  
Yong Ming Kow ◽  
Xinning Gui ◽  
Waikuen Cheng
2020 ◽  
pp. 136843022097475
Author(s):  
Samuel Hansen Freel ◽  
Rezarta Bilali ◽  
Erin Brooke Godfrey

In a three-wave longitudinal study conducted in the first 100 days of Trump’s presidency, this paper examines how people come to self-categorize into the emerging social movement “the Resistance,” and how self-categorization into this movement influences future participation in collective action and perceptions of the movement’s efficacy. Conventional collective action (e.g., protest, lobby legislators)—but not persuasive collective action (e.g., posting on social media)—and perceived identity consolidation efficacy of the movement at Wave 1 predicted a higher likelihood of self-categorization into the movement 1 month later (Wave 2) and 2 months later (Wave 3). Self-categorization into the Resistance predicted two types of higher subsequent movement efficacy perceptions, and helped sustain the effects of conventional collective action and movement efficacy beliefs at Wave 1 on efficacy beliefs at Wave 3. Implications for theory and future research on emerging social movements are discussed.


Author(s):  
P. Tamije Selvy ◽  
V. Suriya Prakash ◽  
S. Shriram ◽  
N. Vimalesh

The number of Social Media users have increased rapidly these days and a lot of valuable as well as non valuable information is shared in the social which is capable of reaching many people in a short period of time and hence the valuable information that are shared in the social media can be used for many types of analysis. In this paper the tweets that are shared in the name of a disaster is taken and then a alert system is build. This alert system gives alert to the users after checking the received data with the centralized database. This paper also gives a comparative study on the algorithm used in extracting the data from the social media which gives us the accuracy rate of different algorithm that can be used for text mining.


2021 ◽  
Vol 12 (3) ◽  
pp. 111-128
Author(s):  
Aljohara Fahad Al Saud

Identifying language affiliation among children for family immigrants is crucial for one’s language identity. This study aimed to determine the role played by Arab families in the Kingdom of Saudi Arabia, Austria, and Britain to attain language affiliation among their children. It also aims to identify the challenges facing families living in these countries in achieving language affiliation among their children. The study population consisted of all the families that live in the Kingdom of Saudi Arabia, in addition to all the Arab families that live in Austria and Britain and the study sample included (120) parents. The researcher adopted the descriptive-analytical approach and used the questionnaire as the study tool. The study reached several results; first, the role played by families in the Kingdom of Saudi Arabia, Austria, and United Kingdom to attain language affiliation among their children got a high degree of response. Second, the challenges facing activating the family’s role in attaining language affiliation of their children in the Kingdom of Saudi Arabia and Austria have got a high degree of response, while in Britain, they obtained a very high degree of response. The study recommended involving all family members in accessing different and creative ways of practicing their native language and activating the role of social media in developing the language affiliation of children.


Author(s):  
Joan Francesc Fondevila Gascón ◽  
Pedro Mir Bernal ◽  
Eva Santana López ◽  
Josep Rom Rodríguez

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